Andrological Dysfunction Signals Increased Cardiometabolic Risk: An Age Stratified, Propensity-Matched Cohort Study

Andrological Dysfunction Signals Increased Cardiometabolic Risk: An Age Stratified, Propensity-Matched Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Andrological Dysfunction Signals Increased Cardiometabolic Risk: An Age Stratified, Propensity-Matched Cohort Study Akhil Muthigi, Gal Saffati, Carlos Riveros, Obinna Obuekwe, Skyler Howell, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7730800/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Andrological dysfunction is traditionally considered within the domain of sexual health, but emerging evidence suggests that it may serve as an early marker for cardiometabolic disease. Utilizing the TriNetX database, we conducted a retrospective cohort study to evaluate the association between erectile dysfunction (ED), low testosterone (low T), and the subsequent development of diabetes, metabolic syndrome (MetS), cardiovascular disease (CVD), hypertension, and obesity. Men were stratified by decade of age (18–30, 31–40, 41–50, 51–60, 61–70) and categorized into cohorts based on diagnoses of ED, low T and both conditions. Subgroup analysis assessed the impact of testosterone replacement therapy (TRT) on outcomes in men with low T. Low T was associated with increased risk of developing all outcomes in all age group except for CVD and hypertension in the 18–30 year old group. TRT was associated with decreased risk of diabetes (HR 0.877, p = 0.023). ED was associated with increased risk of CVD, hypertension and diabetes in all age groups. Young men aged 18–30 with both low T and ED exhibited greater risk of developing obesity and MetS compared to those with ED alone. These findings suggest that andrological dysfunction may represent an early clinical indicator of cardiometabolic disease. Health sciences/Diseases/Cardiovascular diseases Health sciences/Diseases/Metabolic disorders Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Male andrological dysfunction encompasses several conditions, including erectile dysfunction (ED) and low testosterone (low T), which can significantly impact quality of life even in younger men ( 1 – 3 ). While these conditions have traditionally been viewed primarily through the lens of reproductive and sexual health, emerging evidence suggests they may serve as early warning signs for broader systemic health issues, particularly cardiometabolic disorders ( 4 , 5 ). The relationship between andrological dysfunction and cardiometabolic health is of particular interest in young men, as this population is generally considered at low risk for metabolic and cardiovascular disease (CVD). However, recent studies have suggested that the presence of andrological dysfunction in this age group may indicate underlying metabolic perturbations that could manifest as more serious conditions later in life ( 6 , 7 ). Previous research has largely focused on older populations or single andrological conditions, leaving gaps in our understanding of how different types of andrological dysfunction in young men may differentially predict future cardiometabolic risk ( 8 , 9 ). This knowledge gap is particularly significant given the increasing prevalence of both andrological dysfunction and cardiometabolic diseases in younger populations ( 3 , 10 ). We hypothesized that different forms of andrological dysfunction might carry varying degrees of cardiometabolic risk, and that understanding these relationships could help identify young men who might benefit from earlier preventive interventions such as cardiac testing ( 11 ). Therefore, we aimed to characterize the association between two common forms of andrological dysfunction (ED and low T) in men aged 18–70 years and their subsequent development of diabetes (DM), metabolic syndrome (MetS), CVD, hypertension (HTN), and obesity. Materials and Methods Study Design and Data Source We conducted a retrospective cohort analysis utilizing electronic health records supplemented with insurance claims from the TriNetX Research Network (Cambridge, MA, USA). The TriNetX database is a federated database containing anonymized electronic health records of over 300 million patients from participating countries around the world. Information regarding demographics, diagnoses from International Classification of Diseases (ICD-10) codes, and procedures from Current Procedural Terminology (CPT) codes was used for analysis. The use of ICD-10 and CPT codes has been validated across multiple specialties and various procedures ( 12 – 14 ). TriNetX adheres to the Health Insurance Portability and Accountability Act (HIPAA). The process by which the data was de-identified is attested to through a formal determination by a qualified expert as defined in Section § 164.514(b)( 1 ) of the HIPAA Privacy Rule. Because this study used only de-identified patient records and did not involve the collection, use, or transmittal of individually identifiable data, this study was exempted from the Institutional Review Board. As a result, only aggregate patient counts, and statistical summaries are provided to protect all patient health information and retain de-identification. Cohorts and Outcome Measures This study included men aged 18–70 years who had a diagnosis of ED (N52) or low T (E29.1) between July 17, 2005, and July 17, 2025. Controls were selected using propensity score matching, in which individuals with similar probabilities of receiving treatment, based on observed baseline characteristics, are matched to study participants. Matching was performed based on age, race, and pertinent comorbid conditions, including tobacco use (Z72.0), alcohol-related disorders (F10), and disorders of lipoprotein metabolism (E78). Study participants were stratified into age groups by decade: 18–30, 31–40, 41–50, 51–60, and 61–70. Each group was assessed for the development of DM (E11), MetS (E88.81), CVD (I20-I25), HTN (I10), and obesity (E66). The primary outcome was the incidence of individuals who developed each condition. Follow-up continued until the occurrence of the outcome or the end of the study period ( 12 – 14 ). Patients who had the outcomes of interest prior to their index date of andrological dysfunction diagnosis were excluded. A subgroup analysis within the low T cohort was performed to assess the effect of exogenous testosterone on study outcomes. We compared men with low T who were not using testosterone replacement therapy (TRT) with those on TRT, whose testosterone levels had normalized as a benefit of TRT. Statistical Analysis A greedy closest neighbor approach with a caliper width of 0.1 pooled standard deviations was used to match propensity scores in a 1:1 ratio. The TriNetX platform uses a fixed seed to guarantee reproducibility and randomly arranges patient information before matching to reduce selection bias that comes with nearest neighbor algorithms. Based on the determined propensity scores, a matched control was chosen from the larger cohort for every patient in the smaller cohort. Standardized mean differences (SMDs) were used to measure covariate balance between matched groups; residual imbalance was indicated by an absolute SMD > 0.1. Kaplan-Meier survival curves were used for time-to-event analyses, and the survival package's (version 3.2-3) Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% CIs implemented in the survival package (version 3.2-3) in R (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was defined a priori as a two-sided α < 0.05. A prespecified subgroup analysis stratified outcomes by age decade. Results Overall Cohort Characteristics A total of 1 342 347 study participants were compared to an equal number of controls. The low T and ED cohorts included 363 109 and 979 238 participants, respectively. The TRT subgroup analysis contained 17 479 participants. Mean age and other demographics were similar in each cohort. All relevant demographics and comorbidities are summarized in Tables 1–3. The median (IQR) follow up was 2.22 (4.84) years. Low Testosterone Across all age groups, patients with low T exhibited significantly elevated risks for metabolic and cardiovascular comorbidities presented in Fig. 1 . The youngest cohort (18–30 years, n = 14 479) demonstrated the highest risk increases for DM (HR 2.02, 95% CI: 1.67–2.43, p < 0.01), MetS (HR 4.44, 95% CI: 3.19–6.17, p < 0.01), and obesity (HR 1.96, 95% CI: 1.77–2.16, p < 0.01), while no significant association was observed for CVD or HTN. In patients aged 31–40 (n = 41 787), all outcomes were significantly elevated, with notable risks for DM (HR 2.12, 95% CI: 1.93–2.32, p < 0.01), MetS (HR 3.48, 95% CI: 2.87–4.25, p < 0.01), and CVD (HR 1.95, 95% CI: 1.68–2.25, p < 0.01). These patterns persisted and intensified with age. Among those aged 41–50 and 51–60, future development of CVD peaked (HR 2.67 and 2.44, respectively, p < 0.01 for both), along with consistent elevations in HTN and DM. Patients aged 61–70 (n = 113 612) maintained elevated risks for all outcomes, CVD (HR 2.02, 95% CI: 1.97–2.08, p < 0.01), DM (HR 1.91, 95% CI: 1.86–1.96, p < 0.01), and MetS (HR 1.74, 95% CI 1.62–1.87, p < 0.01). TRT Subgroup Analysis When comparing men with low T who received TRT (resulting in normalized testosterone levels) to those who did not, TRT use reduced the incidence of DM: men who did not use TRT had a higher risk of developing DM compared with those using TRT (HR 1.14, 95% CI: 1.06–1.24, p = 0.02). No other differences between cohorts were noted. Erectile Dysfunction ED was associated with elevated risks for cardiovascular diseases in all age brackets (Fig. 2 ). Among 18–30 year-olds (n = 21 219), ED was associated with higher risks for development of DM (HR 1.37, 95% CI: 1.11–1.69, p < 0.01), CVD (HR 1.54, 95% CI: 1.16–2.03, p < 0.01), and HTN (HR 1.17, 95% CI: 1.05–1.30, p < 0.01), while obesity risk was paradoxically reduced (HR 0.88, 95% CI: 0.80–0.97, p < 0.01). Middle-aged groups showed increasing disease burden. In patients aged 31–40 (n = 63 382), ED was strongly associated with CVD (HR 1.93, 95% CI: 1.74–2.16, p < 0.01) and DM (HR 1.48, 95% CI: 1.37–1.59, p < 0.01), with consistent elevations in HTN and obesity. The 41–50 and 51–60 age groups demonstrated nearly identical risk profiles, with pronounced elevations in CVD (HR 2.54, 95% CI 2.42–2.65, p < 0.01) and HTN (HR 1.68, 95% CI: 1.65–1.72, p < 0.01), though MetS was not significantly associated. Older adults (61–70 years) also exhibited sustained elevated risks for CVD (HR 1.83, 95% CI: 1.81–1.85, p < 0.01), HTN (HR 1.45, 95% CI: 1.44–1.47, p < 0.01), and DM (HR 1.44, 95% CI: 1.41–1.46, p < 0.01), although MetS remained statistically insignificant. Combined Andrological Dysfunction When aggregating both andrological conditions, there was a sustained increase in risk of DM, CVD and HTN in all age groups except for HTN in the 18–30 year old group (HR 1.024, p = 0.57), as seen in Fig. 3 . Study participants aged 18–30 had a marked increased risk of DM (HR: 1.261 95% CI: 1.106–1.437, p < 0.01) compared to the ED only group. Discussion This comprehensive analysis of the associations between andrological dysfunction and cardiometabolic outcomes in different age groups reveals different risk profiles with important clinical implications. Our findings demonstrate that low T and ED present unique relationships with metabolic and cardiovascular conditions, with notable age-specific variations. The youngest low T cohort (18–30 years) had the highest risk increases for metabolic syndrome (HR 4.44) and DM (HR 2.02), suggesting that testosterone deficiency may exert its most profound metabolic effects early in adult life. This finding extends previous research that has primarily focused on middle-aged and older populations ( 8 , 9 ). The age-stratified analysis revealed that cardiometabolic risks persist throughout life in hypogonadal men, with CVD risk peaking in middle age (HR 2.67 for ages 41–50), before moderating somewhat in older adults. This pattern suggests potential cumulative damage from long-standing testosterone deficiency. The sustained elevation of all cardiometabolic risks, even in the oldest cohort (61–70 years), underscores the health impact of low T across the patient lifespan. The association between low T and adverse cardiometabolic outcomes observed in our study aligns with existing literature suggesting testosterone's crucial role in metabolic regulation and cardiovascular health ( 15 , 16 ). Previous studies have demonstrated the deleterious effects low T has on multiple organ systems. Low T has been associated with an increased risk of depression, heart failure, anemia, osteoporosis, obesity, insulin resistance, MetS, DM, and fatty liver disease ( 9 , 17 – 22 ). Muraleedharan et al. reported that low T is associated with an increased risk of all-cause mortality ( 8 ). These findings regarding low T are not surprising, given testosterone’s widespread influence on multiple physiological systems within males. Testosterone plays a role in psychological function, affecting libido, mood, cognition, motivation, vitality, and overall sense of well-being ( 18 ). Metabolically, it plays a role in lipid metabolism, energy balance, and body composition ( 18 ). Testosterone also affects the musculoskeletal system by potentiating bone mineral density, muscle mass, physical strength, and stamina ( 18 ). In the hematological system, testosterone stimulates erythropoiesis, while in the endocrinological system, it influences glucose metabolism and insulin sensitivity ( 18 ). In the cardiovascular system, testosterone contributes to endothelial function, vascular tone, blood pressure regulation, as well as sexual effects not listed here ( 18 , 23 ). Given these widespread roles, it is plausible that testosterone deficiency contributes to the development of MetS, CVD, DM, obesity, and HTN. Specifically, low T is associated with hyperlipidemia, increased visceral adiposity, insulin insensitivity, and hyperglycemia, which are all risk factors for MetS, DM, obesity, and CVD ( 18 , 24 , 25 ). Additionally, endothelial dysfunction, elevated blood pressure, hyperlipidemia, and chronic low-grade inflammation accelerates plaque formation, which further increases the risk of developing CVD and HTN ( 18 , 26 ). In this study, TRT use was not associated with differences in outcomes for men with low T except for a reduced risk of developing DM. TRT’s effect on cardiometabolic disease varies in the literature. A meta-analysis of 5 randomized clinical trials showed that TRT use is associated with improved glycemic control in hypogonadal men with DM ( 27 ). Similarly, other studies report improvements in HbA1c, fasting blood glucose, fasting insulin and insulin resistance index (HOMA-IR), triglycerides and waist circumference ( 28 , 29 ). Conversely, another clinical trial found no significant changes in glucose, HbA1c or triglycerides in with TRT compared to placebo ( 30 ). The Endocrine Society clinical practice guidelines state that there is no conclusive association between TRT use and cardiovascular risk or major cardiovascular events ( 31 ). It is plausible that TRT alone has limited effect on cardiometabolic outcomes unless combined with positive lifestyle changes ( 32 ). Our findings regarding ED reinforce its well-established role as an early marker of cardiovascular pathology ( 33 , 34 ). The significant association between ED and CVD even in young adults (HR 1.54 for ages 18–30) supports the "artery size hypothesis," which states that endothelial dysfunction affects penile arteries earlier than larger coronary vessels due to their smaller diameter ( 33 ). This provides further evidence that ED may precede clinically evident CVD by several years, offering a valuable window for preventive intervention. Study participants with both ED and low T had increased risks of developing CVD, HTN and DM, consistent with findings in the individual low T and ED cohorts. In 18–30 year olds with both conditions, the risk of developing obesity and MetS was also increased in comparison to having ED alone, highlighting the deleterious effects low T has on multiple organ systems ( 18 ). These findings have several important clinical implications. First, they support expanded metabolic screening for young men presenting with low T, given the remarkably high and relatively immediate risks for DM and MetS in this population. Second, they reinforce the value of cardiovascular risk assessment in men with ED, even at young ages when traditional cardiovascular risk calculation algorithms may underestimate risk. Several limitations must be acknowledged. First, as an observational study using electronic health records, causality between andrological dysfunction and cardiometabolic outcomes cannot be established. Second, diagnostic coding may not fully capture the severity or duration of andrological conditions, potentially biasing dose-dependent relationships. Additionally, due to the nature of TriNetX, there was no specific data on hormone values, or penile doppler data to confirm low T and ED. Third, while key confounders were adjusted for, residual confounding from unmeasured factors not readily available in the database, such as physical activity, dietary patterns, socioeconomic status, and changes in behavior after andrological disease diagnosis, cannot be excluded. Fourth, the short median follow-up duration, which was 2 years and 10 months on average, may have underrepresented the incidence of future development of cardiometabolic disease. Except for the low T cohort, treatment with TRT was not accounted for. Despite propensity score matching, several baseline covariates retained standardized mean differences > 0.10, indicating residual imbalance. Consequently, residual confounding may persist and could bias the effect estimates in either direction. These results should be interpreted as associations rather than direct causal effects. This large-scale, age-stratified analysis demonstrates that andrological dysfunction exhibits distinct and age-dependent associations with cardiometabolic outcomes. Low T and ED consistently predict adverse cardiometabolic health, with risk patterns varying across the lifespan. These findings support the potential integration of reproductive and cardiometabolic health assessments in clinical practice and highlight the importance of early identification and management of these conditions, particularly in younger men where preventive interventions may yield the greatest long-term benefit. Future prospective work with longer term follow-up is required to validate these results as well as determine which specific age groups would benefit the most from early screening and intervention. Abbreviations CPT Current procedural terminology CVD Cardiovascular disease DM Diabetes Mellitus ED Erectile dysfunction HIPAA Health Insurance Portability and Accountability Act HTN Hypertension ICD 10–International Classification of Diseases, 10th Revision Low T Low testosterone MetS Metabolic syndrome TRT Testosterone replacement therapy Declarations Data Availability Statement All data generated or analyzed during this study are included in this published article . Acknowledgements No financial assistance was received in support of this study. Author Contribution Statement Gal Saffati, Obinna Obuekwe, and Skyler Howell wrote the original draft and played important roles in interpreting the results. Carlos Riveros was responsible for methodology, investigation, data curation and formal analysis. Nick Deebel, Taylor Kohn, and Akhil Muthigi were responsible for conceptualization, validation, review & editing, supervision, and project administration. All authors approve the final version of this manuscript and agree to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Funding No financial assistance was received in support of this study. Ethical Approval Institutional Review Board (IRB) approval was not required for this study as it involved the analysis of previously collected de-identified data. The dataset contained no personal identifiers, and no link could be made back to individual subjects. According to the United States Department of Health and Human Services, research using de-identified secondary data that cannot be traced back to individuals is not considered human subjects research and is exempt from IRB review (Common Rule 45 CFR 46.104(d)(4)). Informed consent was waived due to the anonymous nature of the dataset and absence of any interaction with human subjects. 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Supplementary Files Table1LowT.xlsx Table 1 Table2TRT.xlsx Table 2 Table3ED.xlsx Table 3 Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: revise 05 Jan, 2026 Review # 2 received at journal 21 Oct, 2025 Reviewer # 2 agreed at journal 14 Oct, 2025 Review # 1 received at journal 13 Oct, 2025 Reviewer # 1 agreed at journal 13 Oct, 2025 Reviewers invited by journal 05 Oct, 2025 Submission checks completed at journal 29 Sep, 2025 Editor assigned by journal 27 Sep, 2025 First submitted to journal 27 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7730800","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":524917906,"identity":"b474f5b2-897f-4355-a256-58d4fe1f8ff9","order_by":0,"name":"Akhil 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Medicine","correspondingAuthor":false,"prefix":"","firstName":"Gal","middleName":"","lastName":"Saffati","suffix":""},{"id":524917908,"identity":"59dcd79e-7a24-4537-bc09-2fc3669b1890","order_by":2,"name":"Carlos Riveros","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Carlos","middleName":"","lastName":"Riveros","suffix":""},{"id":524917909,"identity":"2573985b-1b76-4977-bc1c-2f801da74d77","order_by":3,"name":"Obinna Obuekwe","email":"","orcid":"https://orcid.org/0009-0000-7202-0076","institution":"Houston Methodist Hospital","correspondingAuthor":false,"prefix":"","firstName":"Obinna","middleName":"","lastName":"Obuekwe","suffix":""},{"id":524917910,"identity":"cd6b6846-44aa-4bd7-9c72-87bd7840b082","order_by":4,"name":"Skyler Howell","email":"","orcid":"","institution":"University of Texas Health Science Center-Houston/McGovern Medical School","correspondingAuthor":false,"prefix":"","firstName":"Skyler","middleName":"","lastName":"Howell","suffix":""},{"id":524917911,"identity":"fb20abd2-d642-4e69-8565-72a99c08ec05","order_by":5,"name":"Nicholas Deebel","email":"","orcid":"","institution":"Northwestern University Feinberg School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Deebel","suffix":""},{"id":524917912,"identity":"e94d6bed-4686-4af8-977b-68d92909b99a","order_by":6,"name":"Taylor Kohn","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Taylor","middleName":"","lastName":"Kohn","suffix":""}],"badges":[],"createdAt":"2025-09-28 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1","display":"","copyAsset":false,"role":"figure","size":45725,"visible":true,"origin":"","legend":"\u003cp\u003eHazard ratios for chronic disease development in men with low testosterone by age group\u003c/p\u003e","description":"","filename":"Figure1LowT.png","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/22bc3f9900b90d6491f8d0f9.png"},{"id":93676705,"identity":"15231037-f0ba-4815-92fb-63c6900a2ce7","added_by":"auto","created_at":"2025-10-16 11:14:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46666,"visible":true,"origin":"","legend":"\u003cp\u003eHazard ratios for chronic disease development in men with erectile dysfunction by age group\u003c/p\u003e","description":"","filename":"Figure2ED.png","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/87870f792cf80766375bbb50.png"},{"id":93676708,"identity":"3bdfa8ee-c2de-4be5-940d-33233ac8ef5f","added_by":"auto","created_at":"2025-10-16 11:14:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":49938,"visible":true,"origin":"","legend":"\u003cp\u003eHazard ratios for chronic disease development in men with low testosterone and erectile dysfunction by age group\u003c/p\u003e","description":"","filename":"Figure3Combined.png","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/e205367c2af5d93097f63b6f.png"},{"id":93677054,"identity":"e12f027a-f97a-4c85-a598-eae18447b1b3","added_by":"auto","created_at":"2025-10-16 11:22:27","extension":"pdf","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":48028,"visible":true,"origin":"","legend":"Hazard ratios for chronic disease development in men with low testosterone and erectile dysfunction by age group","description":"","filename":"Figure3Combined.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/d8c6b6d041e0d3cdcaf3a44d.pdf"},{"id":93678395,"identity":"a5604811-ee5a-4b48-be18-e9e5ce2639e6","added_by":"auto","created_at":"2025-10-16 11:38:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":645196,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/0ad5202a-49e0-4c98-a12f-8d14c8dd0e94.pdf"},{"id":93677053,"identity":"0777f431-7553-4eb7-82bb-231bf7573b44","added_by":"auto","created_at":"2025-10-16 11:22:27","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10956,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1\u003c/p\u003e","description":"","filename":"Table1LowT.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/e1d17d9e10772a4c64d0275d.xlsx"},{"id":93676710,"identity":"4444b738-01c9-45e1-9236-9a05773a1f2f","added_by":"auto","created_at":"2025-10-16 11:14:27","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10933,"visible":true,"origin":"","legend":"\u003cp\u003eTable 2\u003c/p\u003e","description":"","filename":"Table2TRT.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/f9218db7f39aa4cd391dc74b.xlsx"},{"id":93676714,"identity":"68a1db6e-0a09-435f-b84c-9def2d6d90e4","added_by":"auto","created_at":"2025-10-16 11:14:27","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":10996,"visible":true,"origin":"","legend":"Table 3","description":"","filename":"Table3ED.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7730800/v1/6dd818bb4408a43fd06bd4a3.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Andrological Dysfunction Signals Increased Cardiometabolic Risk: An Age Stratified, Propensity-Matched Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMale andrological dysfunction encompasses several conditions, including erectile dysfunction (ED) and low testosterone (low T), which can significantly impact quality of life even in younger men (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). While these conditions have traditionally been viewed primarily through the lens of reproductive and sexual health, emerging evidence suggests they may serve as early warning signs for broader systemic health issues, particularly cardiometabolic disorders (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The relationship between andrological dysfunction and cardiometabolic health is of particular interest in young men, as this population is generally considered at low risk for metabolic and cardiovascular disease (CVD). However, recent studies have suggested that the presence of andrological dysfunction in this age group may indicate underlying metabolic perturbations that could manifest as more serious conditions later in life (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePrevious research has largely focused on older populations or single andrological conditions, leaving gaps in our understanding of how different types of andrological dysfunction in young men may differentially predict future cardiometabolic risk (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). This knowledge gap is particularly significant given the increasing prevalence of both andrological dysfunction and cardiometabolic diseases in younger populations (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe hypothesized that different forms of andrological dysfunction might carry varying degrees of cardiometabolic risk, and that understanding these relationships could help identify young men who might benefit from earlier preventive interventions such as cardiac testing (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Therefore, we aimed to characterize the association between two common forms of andrological dysfunction (ED and low T) in men aged 18\u0026ndash;70 years and their subsequent development of diabetes (DM), metabolic syndrome (MetS), CVD, hypertension (HTN), and obesity.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Data Source\u003c/h2\u003e\u003cp\u003eWe conducted a retrospective cohort analysis utilizing electronic health records supplemented with insurance claims from the TriNetX Research Network (Cambridge, MA, USA). The TriNetX database is a federated database containing anonymized electronic health records of over 300\u0026nbsp;million patients from participating countries around the world. Information regarding demographics, diagnoses from International Classification of Diseases (ICD-10) codes, and procedures from Current Procedural Terminology (CPT) codes was used for analysis. The use of ICD-10 and CPT codes has been validated across multiple specialties and various procedures (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTriNetX adheres to the Health Insurance Portability and Accountability Act (HIPAA). The process by which the data was de-identified is attested to through a formal determination by a qualified expert as defined in Section \u0026sect;\u0026nbsp;164.514(b)(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) of the HIPAA Privacy Rule. Because this study used only de-identified patient records and did not involve the collection, use, or transmittal of individually identifiable data, this study was exempted from the Institutional Review Board. As a result, only aggregate patient counts, and statistical summaries are provided to protect all patient health information and retain de-identification.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCohorts and Outcome Measures\u003c/h3\u003e\n\u003cp\u003eThis study included men aged 18\u0026ndash;70 years who had a diagnosis of ED (N52) or low T (E29.1) between July 17, 2005, and July 17, 2025. Controls were selected using propensity score matching, in which individuals with similar probabilities of receiving treatment, based on observed baseline characteristics, are matched to study participants. Matching was performed based on age, race, and pertinent comorbid conditions, including tobacco use (Z72.0), alcohol-related disorders (F10), and disorders of lipoprotein metabolism (E78).\u003c/p\u003e\u003cp\u003eStudy participants were stratified into age groups by decade: 18\u0026ndash;30, 31\u0026ndash;40, 41\u0026ndash;50, 51\u0026ndash;60, and 61\u0026ndash;70. Each group was assessed for the development of DM (E11), MetS (E88.81), CVD (I20-I25), HTN (I10), and obesity (E66). The primary outcome was the incidence of individuals who developed each condition. Follow-up continued until the occurrence of the outcome or the end of the study period (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Patients who had the outcomes of interest prior to their index date of andrological dysfunction diagnosis were excluded.\u003c/p\u003e\u003cp\u003eA subgroup analysis within the low T cohort was performed to assess the effect of exogenous testosterone on study outcomes. We compared men with low T who were not using testosterone replacement therapy (TRT) with those on TRT, whose testosterone levels had normalized as a benefit of TRT.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eA greedy closest neighbor approach with a caliper width of 0.1 pooled standard deviations was used to match propensity scores in a 1:1 ratio. The TriNetX platform uses a fixed seed to guarantee reproducibility and randomly arranges patient information before matching to reduce selection bias that comes with nearest neighbor algorithms. Based on the determined propensity scores, a matched control was chosen from the larger cohort for every patient in the smaller cohort.\u003c/p\u003e\u003cp\u003eStandardized mean differences (SMDs) were used to measure covariate balance between matched groups; residual imbalance was indicated by an absolute SMD\u0026thinsp;\u0026gt;\u0026thinsp;0.1. Kaplan-Meier survival curves were used for time-to-event analyses, and the survival package's (version 3.2-3) Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% CIs implemented in the survival package (version 3.2-3) in R (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was defined a priori as a two-sided α\u0026thinsp;\u0026lt;\u0026thinsp;0.05. A prespecified subgroup analysis stratified outcomes by age decade.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eOverall Cohort Characteristics\u003c/h2\u003e\u003cp\u003eA total of 1 342 347 study participants were compared to an equal number of controls. The low T and ED cohorts included 363 109 and 979 238 participants, respectively. The TRT subgroup analysis contained 17 479 participants. Mean age and other demographics were similar in each cohort. All relevant demographics and comorbidities are summarized in Tables\u0026nbsp;1\u0026ndash;3. The median (IQR) follow up was 2.22 (4.84) years.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eLow Testosterone\u003c/h2\u003e\u003cp\u003eAcross all age groups, patients with low T exhibited significantly elevated risks for metabolic and cardiovascular comorbidities presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The youngest cohort (18\u0026ndash;30 years, n\u0026thinsp;=\u0026thinsp;14 479) demonstrated the highest risk increases for DM (HR 2.02, 95% CI: 1.67\u0026ndash;2.43, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), MetS (HR 4.44, 95% CI: 3.19\u0026ndash;6.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and obesity (HR 1.96, 95% CI: 1.77\u0026ndash;2.16, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while no significant association was observed for CVD or HTN. In patients aged 31\u0026ndash;40 (n\u0026thinsp;=\u0026thinsp;41 787), all outcomes were significantly elevated, with notable risks for DM (HR 2.12, 95% CI: 1.93\u0026ndash;2.32, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), MetS (HR 3.48, 95% CI: 2.87\u0026ndash;4.25, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and CVD (HR 1.95, 95% CI: 1.68\u0026ndash;2.25, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These patterns persisted and intensified with age. Among those aged 41\u0026ndash;50 and 51\u0026ndash;60, future development of CVD peaked (HR 2.67 and 2.44, respectively, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for both), along with consistent elevations in HTN and DM. Patients aged 61\u0026ndash;70 (n\u0026thinsp;=\u0026thinsp;113 612) maintained elevated risks for all outcomes, CVD (HR 2.02, 95% CI: 1.97\u0026ndash;2.08, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), DM (HR 1.91, 95% CI: 1.86\u0026ndash;1.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and MetS (HR 1.74, 95% CI 1.62\u0026ndash;1.87, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTRT Subgroup Analysis\u003c/h3\u003e\n\u003cp\u003eWhen comparing men with low T who received TRT (resulting in normalized testosterone levels) to those who did not, TRT use reduced the incidence of DM: men who did not use TRT had a higher risk of developing DM compared with those using TRT (HR 1.14, 95% CI: 1.06\u0026ndash;1.24, p\u0026thinsp;=\u0026thinsp;0.02). No other differences between cohorts were noted.\u003c/p\u003e\n\u003ch3\u003eErectile Dysfunction\u003c/h3\u003e\n\u003cp\u003eED was associated with elevated risks for cardiovascular diseases in all age brackets (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among 18\u0026ndash;30 year-olds (n\u0026thinsp;=\u0026thinsp;21 219), ED was associated with higher risks for development of DM (HR 1.37, 95% CI: 1.11\u0026ndash;1.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), CVD (HR 1.54, 95% CI: 1.16\u0026ndash;2.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and HTN (HR 1.17, 95% CI: 1.05\u0026ndash;1.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while obesity risk was paradoxically reduced (HR 0.88, 95% CI: 0.80\u0026ndash;0.97, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Middle-aged groups showed increasing disease burden. In patients aged 31\u0026ndash;40 (n\u0026thinsp;=\u0026thinsp;63 382), ED was strongly associated with CVD (HR 1.93, 95% CI: 1.74\u0026ndash;2.16, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and DM (HR 1.48, 95% CI: 1.37\u0026ndash;1.59, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with consistent elevations in HTN and obesity. The 41\u0026ndash;50 and 51\u0026ndash;60 age groups demonstrated nearly identical risk profiles, with pronounced elevations in CVD (HR 2.54, 95% CI 2.42\u0026ndash;2.65, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and HTN (HR 1.68, 95% CI: 1.65\u0026ndash;1.72, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), though MetS was not significantly associated. Older adults (61\u0026ndash;70 years) also exhibited sustained elevated risks for CVD (HR 1.83, 95% CI: 1.81\u0026ndash;1.85, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), HTN (HR 1.45, 95% CI: 1.44\u0026ndash;1.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and DM (HR 1.44, 95% CI: 1.41\u0026ndash;1.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), although MetS remained statistically insignificant.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eCombined Andrological Dysfunction\u003c/h2\u003e\u003cp\u003eWhen aggregating both andrological conditions, there was a sustained increase in risk of DM, CVD and HTN in all age groups except for HTN in the 18\u0026ndash;30 year old group (HR 1.024, p\u0026thinsp;=\u0026thinsp;0.57), as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Study participants aged 18\u0026ndash;30 had a marked increased risk of DM (HR: 1.261 95% CI: 1.106\u0026ndash;1.437, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to the ED only group.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis comprehensive analysis of the associations between andrological dysfunction and cardiometabolic outcomes in different age groups reveals different risk profiles with important clinical implications. Our findings demonstrate that low T and ED present unique relationships with metabolic and cardiovascular conditions, with notable age-specific variations.\u003c/p\u003e\u003cp\u003eThe youngest low T cohort (18\u0026ndash;30 years) had the highest risk increases for metabolic syndrome (HR 4.44) and DM (HR 2.02), suggesting that testosterone deficiency may exert its most profound metabolic effects early in adult life. This finding extends previous research that has primarily focused on middle-aged and older populations (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The age-stratified analysis revealed that cardiometabolic risks persist throughout life in hypogonadal men, with CVD risk peaking in middle age (HR 2.67 for ages 41\u0026ndash;50), before moderating somewhat in older adults. This pattern suggests potential cumulative damage from long-standing testosterone deficiency. The sustained elevation of all cardiometabolic risks, even in the oldest cohort (61\u0026ndash;70 years), underscores the health impact of low T across the patient lifespan.\u003c/p\u003e\u003cp\u003eThe association between low T and adverse cardiometabolic outcomes observed in our study aligns with existing literature suggesting testosterone's crucial role in metabolic regulation and cardiovascular health (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Previous studies have demonstrated the deleterious effects low T has on multiple organ systems. Low T has been associated with an increased risk of depression, heart failure, anemia, osteoporosis, obesity, insulin resistance, MetS, DM, and fatty liver disease (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Muraleedharan et al. reported that low T is associated with an increased risk of all-cause mortality (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese findings regarding low T are not surprising, given testosterone\u0026rsquo;s widespread influence on multiple physiological systems within males. Testosterone plays a role in psychological function, affecting libido, mood, cognition, motivation, vitality, and overall sense of well-being (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Metabolically, it plays a role in lipid metabolism, energy balance, and body composition (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Testosterone also affects the musculoskeletal system by potentiating bone mineral density, muscle mass, physical strength, and stamina (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In the hematological system, testosterone stimulates erythropoiesis, while in the endocrinological system, it influences glucose metabolism and insulin sensitivity (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In the cardiovascular system, testosterone contributes to endothelial function, vascular tone, blood pressure regulation, as well as sexual effects not listed here (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Given these widespread roles, it is plausible that testosterone deficiency contributes to the development of MetS, CVD, DM, obesity, and HTN. Specifically, low T is associated with hyperlipidemia, increased visceral adiposity, insulin insensitivity, and hyperglycemia, which are all risk factors for MetS, DM, obesity, and CVD (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Additionally, endothelial dysfunction, elevated blood pressure, hyperlipidemia, and chronic low-grade inflammation accelerates plaque formation, which further increases the risk of developing CVD and HTN (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, TRT use was not associated with differences in outcomes for men with low T except for a reduced risk of developing DM. TRT\u0026rsquo;s effect on cardiometabolic disease varies in the literature. A meta-analysis of 5 randomized clinical trials showed that TRT use is associated with improved glycemic control in hypogonadal men with DM (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Similarly, other studies report improvements in HbA1c, fasting blood glucose, fasting insulin and insulin resistance index (HOMA-IR), triglycerides and waist circumference (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Conversely, another clinical trial found no significant changes in glucose, HbA1c or triglycerides in with TRT compared to placebo (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The Endocrine Society clinical practice guidelines state that there is no conclusive association between TRT use and cardiovascular risk or major cardiovascular events (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). It is plausible that TRT alone has limited effect on cardiometabolic outcomes unless combined with positive lifestyle changes (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur findings regarding ED reinforce its well-established role as an early marker of cardiovascular pathology (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The significant association between ED and CVD even in young adults (HR 1.54 for ages 18\u0026ndash;30) supports the \"artery size hypothesis,\" which states that endothelial dysfunction affects penile arteries earlier than larger coronary vessels due to their smaller diameter (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). This provides further evidence that ED may precede clinically evident CVD by several years, offering a valuable window for preventive intervention.\u003c/p\u003e\u003cp\u003eStudy participants with both ED and low T had increased risks of developing CVD, HTN and DM, consistent with findings in the individual low T and ED cohorts. In 18\u0026ndash;30 year olds with both conditions, the risk of developing obesity and MetS was also increased in comparison to having ED alone, highlighting the deleterious effects low T has on multiple organ systems (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese findings have several important clinical implications. First, they support expanded metabolic screening for young men presenting with low T, given the remarkably high and relatively immediate risks for DM and MetS in this population. Second, they reinforce the value of cardiovascular risk assessment in men with ED, even at young ages when traditional cardiovascular risk calculation algorithms may underestimate risk.\u003c/p\u003e\u003cp\u003eSeveral limitations must be acknowledged. First, as an observational study using electronic health records, causality between andrological dysfunction and cardiometabolic outcomes cannot be established. Second, diagnostic coding may not fully capture the severity or duration of andrological conditions, potentially biasing dose-dependent relationships. Additionally, due to the nature of TriNetX, there was no specific data on hormone values, or penile doppler data to confirm low T and ED. Third, while key confounders were adjusted for, residual confounding from unmeasured factors not readily available in the database, such as physical activity, dietary patterns, socioeconomic status, and changes in behavior after andrological disease diagnosis, cannot be excluded. Fourth, the short median follow-up duration, which was 2 years and 10 months on average, may have underrepresented the incidence of future development of cardiometabolic disease. Except for the low T cohort, treatment with TRT was not accounted for. Despite propensity score matching, several baseline covariates retained standardized mean differences\u0026thinsp;\u0026gt;\u0026thinsp;0.10, indicating residual imbalance. Consequently, residual confounding may persist and could bias the effect estimates in either direction. These results should be interpreted as associations rather than direct causal effects.\u003c/p\u003e\u003cp\u003eThis large-scale, age-stratified analysis demonstrates that andrological dysfunction exhibits distinct and age-dependent associations with cardiometabolic outcomes. Low T and ED consistently predict adverse cardiometabolic health, with risk patterns varying across the lifespan. These findings support the potential integration of reproductive and cardiometabolic health assessments in clinical practice and highlight the importance of early identification and management of these conditions, particularly in younger men where preventive interventions may yield the greatest long-term benefit. Future prospective work with longer term follow-up is required to validate these results as well as determine which specific age groups would benefit the most from early screening and intervention.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCPT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCurrent procedural terminology\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCVD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCardiovascular disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDiabetes Mellitus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eED\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eErectile dysfunction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHIPAA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHealth Insurance Portability and Accountability Act\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHTN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e10\u0026ndash;International Classification of Diseases, 10th Revision\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLow T\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLow testosterone\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMetS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMetabolic syndrome\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTRT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTestosterone replacement therapy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003epublished article\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo financial assistance was received in support of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGal Saffati, Obinna Obuekwe, and Skyler Howell wrote the original draft and played important roles in interpreting the results. Carlos Riveros was responsible for methodology, investigation, data curation and formal analysis. Nick Deebel, Taylor Kohn, and Akhil Muthigi were responsible for conceptualization, validation, review \u0026amp; editing, supervision, and project administration. All authors approve the final version of this manuscript and agree to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo financial assistance was received in support of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstitutional Review Board (IRB) approval was not required for this study as it involved the analysis of previously collected de-identified data. The dataset contained no personal identifiers, and no link could be made back to individual subjects. According to the United States Department of Health and Human Services, research using de-identified secondary data that cannot be traced back to individuals is not considered human subjects research and is exempt from IRB review (Common Rule 45 CFR 46.104(d)(4)). Informed consent was waived due to the anonymous nature of the dataset and absence of any interaction with human subjects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest to disclose. This article represents independent research, and we affirm that no external funding or commercial support has been involved in the preparation of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCohen J, Nassau DE, Patel P, Ramasamy R. 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European Heart Journal. 2013 July 1;34(27):2034\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-impotence-research","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ijir","sideBox":"Learn more about [International Journal of Impotence Research](http://www.nature.com/ijir/)","snPcode":"41443","submissionUrl":"https://mts-ijir.nature.com/cgi-bin/main.plex","title":"International Journal of Impotence Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7730800/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7730800/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAndrological dysfunction is traditionally considered within the domain of sexual health, but emerging evidence suggests that it may serve as an early marker for cardiometabolic disease. Utilizing the TriNetX database, we conducted a retrospective cohort study to evaluate the association between erectile dysfunction (ED), low testosterone (low T), and the subsequent development of diabetes, metabolic syndrome (MetS), cardiovascular disease (CVD), hypertension, and obesity. Men were stratified by decade of age (18\u0026ndash;30, 31\u0026ndash;40, 41\u0026ndash;50, 51\u0026ndash;60, 61\u0026ndash;70) and categorized into cohorts based on diagnoses of ED, low T and both conditions. Subgroup analysis assessed the impact of testosterone replacement therapy (TRT) on outcomes in men with low T. Low T was associated with increased risk of developing all outcomes in all age group except for CVD and hypertension in the 18\u0026ndash;30 year old group. TRT was associated with decreased risk of diabetes (HR 0.877, p\u0026thinsp;=\u0026thinsp;0.023). ED was associated with increased risk of CVD, hypertension and diabetes in all age groups. Young men aged 18\u0026ndash;30 with both low T and ED exhibited greater risk of developing obesity and MetS compared to those with ED alone. These findings suggest that andrological dysfunction may represent an early clinical indicator of cardiometabolic disease.\u003c/p\u003e","manuscriptTitle":"Andrological Dysfunction Signals Increased Cardiometabolic Risk: An Age Stratified, Propensity-Matched Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 11:14:22","doi":"10.21203/rs.3.rs-7730800/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-01-05T15:25:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-21T11:00:45+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-14T09:26:54+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-10-13T07:59:57+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-10-13T07:23:03+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-10-05T14:05:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-29T10:14:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-28T00:17:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Impotence Research","date":"2025-09-28T00:17:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-impotence-research","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ijir","sideBox":"Learn more about [International Journal of Impotence Research](http://www.nature.com/ijir/)","snPcode":"41443","submissionUrl":"https://mts-ijir.nature.com/cgi-bin/main.plex","title":"International Journal of Impotence Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"844fe166-2f9b-4d5b-9860-59c551e71a48","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55788899,"name":"Health sciences/Diseases/Cardiovascular diseases"},{"id":55788900,"name":"Health sciences/Diseases/Metabolic disorders"}],"tags":[],"updatedAt":"2026-05-08T10:41:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-16 11:14:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7730800","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7730800","identity":"rs-7730800","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}